Microscopic-scale magnetic recording of brain neuronal electrical activity using a diamond quantum sensor

Quantum sensors using solid state qubits have demonstrated outstanding sensitivity, beyond that possible using classical devices. In particular, those based on colour centres in diamond have demonstrated high sensitivity to magnetic field through exploiting the field-dependent emission of fluorescence under coherent control using microwaves. Given the highly biocompatible nature of diamond, sensing from biological samples is a key interdisciplinary application. In particular, the microscopic-scale study of living systems can be possible through recording of temperature and biomagnetic field. In this work, we use such a quantum sensor to demonstrate such microscopic-scale recording of electrical activity from neurons in fragile living brain tissue. By recording weak magnetic field induced by ionic currents in mouse corpus callosum axons, we accurately recover signals from neuronal action potential propagation while demonstrating in situ pharmacology. Our sensor allows recording of the electrical activity in neural circuits, disruption of which can shed light on the mechanisms of disease emergence. Unlike existing techniques for recording activity, which can require potentially damaging direct interaction, our sensing is entirely passive and remote from the sample. Our results open a promising new avenue for the microscopic recording of neuronal signals, offering the eventual prospect of microscopic imaging of electrical activity in the living mammalian brain.

with an acquisition bandwidth of approximately 10kHz, limited by lock-in amplier low pass frequency (time constant). Based on the collected uorescence power (5-6mW), we estimated the shot noise limited sensitivity to be 16nT p Hz. We plot this level as the dashed red line on the above gure, assuming a at white noise spectrum. The gap between the shot noise level and the measured sensitivity we attribute to imperfect rejection of common mode (predominantly laser technical) noise by our balanced detector, as well as magnetic noise from the laboratory background. Here the main source is from electrical mains (50Hz) and inductive transformer harmonics (mainly at 150Hz). The frequency distribution of the mains noise is broadened by mains phase drift. Based on this measured noise level, our single shot magnetic eld measurement noise without any removal of background magnetic noise is approximately 2T using a sensing bandwidth of 10kHz and 150nT when constraining bandwidth to 2.5kHz by short pass ltering. By implementing de-noising in post-processing, this can be reduced to 7nT and 3nT for 10kHz and 2.5kHz respectively. This is only possi-ble thanks to the large dynamic range of the NV sensor. Alternative sensing platforms (in particular those based on atomic vapour) can be saturated by the high level of background magnetic noise.

Control Slice: No Tetrodotoxin
Supplementary Figure 2: Control measurements for a brain slice without the addition of TTX. Magnetic eld data from the sensor is shown in a) and reference electrical data in b).
Supplementary Figure 2 shows the biological signal as a function of time with zero tetrodotoxin (TTX) added to the solution bath. Data is shown for the rst 3 hours of recording. The signal was observed to slowly decay in amplitude over time as the slice slowly died, with increased latency of the signal component S2.

Minimisation of Stimulation Artifact
As typically observed in electrophysiology experiments, electrical tissue stimulation also induces a stimulation artifact resulting from stimulation current propagation in the tissue and solution bath. This was also observed in the magnetic data from our quantum sensor. Such an artifact poses a problem for digital ltering, the sharp pulse of the stimulation artifact inducing ringing artifacts eects in the ltered data. This is exemplied in Supplementary  Figures 4,a)  The amplitude of such spike is one order of magnitude larger then the biological response from the corpus callosum. b) Comparison of the same stimulation spike shown in a) before and after applying a lowpass lter with a 3 kHz cuto frequency. As a result of the ltering, ringing artifacts are generated before and after the spike. c) Cropped stimulation spike used for subtraction. d) Comparison of the same single-shot time trace after applying spike subtraction and low-pass lter (blue), interpolation (orange) and smoothing (green).
at 3 kHz was applied to an example stimulation event. The unmistakable oscillating ringing artifacts caused by the ltering are visible, with amplitudes in the order of hundreds of picotesla.
In order to tackle this problem, we therefore post-processed our magnetic data to remove stimulation artifacts in a process detailed in Supplementary Figures 3 and 4,c) and d). In brief, the average signal spike caused by the stimulations was rst identied in the time domain and and subtracted from each individual stimulation event in the magnetic data, before applying the majority of signal ltering in the frequency domain. Any residual artifact remaining was then removed by interpolation in the time domain. This approach is a standard, well established method in the electrophysiology literature for stimulation artifact removal. However, here we face unique challenges: in particular the presence of a high level of magnetic background noise and far lower signal level in our magnetic data. This required a modied method for artifact removal.
Identication of the stimulation artifact was carried out by attenuating background mains noise using digital notch lters at 50, 150 and 250 Hz, followed by averaging 60 time traces of 60s at time, for a total of 7000 stimulations. This was necessary to reduce the background mains noise below the artifact level (several nT) while retaining sensing bandwidth (10 kHz). Using this averaged data, we then dened the duration of the artifact as the interval between the stimulation trigger (at t=0sec) and the second zero-crossing of the signal after the peak (Supplementary Figure 4,c).
The averaged artifact signal present in this interval was then cropped and subtracted from each stimulation event in all the magnetic data averaged for the identication process. We note that the success of this procedure relies on the amplitude and duration of the artifact for each stimulation event to be relatively consistent and close to the mean average stimulation artifact. We found this to be the case in the experiments in this work, with variation in amplitude of less than 10%. After the subtraction, the time traces were ltered in the frequency domain to remove noise (as described in Methods).
As we subtract only the average artifact, we note that the subtraction process leaves a residual stimulation artifact, as a result of the imperfect subtraction from each stimulation event of the averaged response. To remove this residual, the magnetic data was further processed by masking the time intervals containing the artifacts, of mask duration earlier obtained during the peak identication process. The signal between these masked sections was then interpolated using 1st order spline interpolation (Supplementary Figure 4,d), with this interpolated data replacing the masked artifact sections in the magnetic data. Finally, a Savitskzy-Golay lter was then applied to each 60s timeseries of this processed magnetic data to smooth the edges of the interpolation intervals.
For completeness, in Supplementary Figures 6-8 we show that the biological signal can be observed with minimal postprocessing and ltering and without artifact removal, employing only a lowpass lter at 6kHz and notch lters at mains harmonics (50,150,250Hz). This removes the majority of the background magnetic noise which obscures the signal (see Sup-plementary Figure 5). The ringing artifacts as a result of retaining the stimulation artifact can be seen, partially obscuring the biological signal.
Supplementary Figure 5: Data for Slice 1 with no ltering or stimulation artifact removal on either the electric or the magnetic data, only averaging for each concentration of TTX. For the magnetic data, any biological signal is entirely obscured by background magnetic noise, primarily at 50Hz and higher mains harmonics. Electrical capacitive pickup of 50Hz on the electrical probe readout also eliminates the biological signal, leaving only a residual stimulation artifact.